Binary Tree Block Encoding of Classical Matrix

State preparation and block-encoding are essential subroutines in quantum computing. The former provides basic encoding of quantum states, while the latter transforms classical data into a matrix representation within a quantum circuit. Some quantum advantages are built on the assumption that the subroutine– block encoding has been compiled in the quantum circuit, and this derives a problem of how to efficiently compile a block encoding. The resource trade-offs of block encoding, such as circuit size, subnormalization factor, compilation complexity (both time and space), and robustness against errors are central to its efficiency. In this work, the Binary Tree Block-Encoding (BITBLE) protocol is introduced, which optimizes these trade-offs. For a classical matrix in C<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2n× 2n</sup>, our approach reduces the compilation time to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i>(n2<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2n</sup>) using n ancilla qubits, achieving superior resource trade-offs compared to existing methods. Numerical experiments further reveal that the approach outlined in BITBLE enhances compilation efficiency, resource scalability, and robustness against single-qubit gate errors in various standard data encoding tasks. Moreover, all algorithms are available as open-source.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Quantum Engineering
Published
2025-10-23
DOI
https://doi.org/10.1109/tqe.2025.3624699
Citations
1
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
1.50
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Binary Tree Block Encoding of Classical Matrix

Zexian Li, Xiaoming Zhang, Guofeng Zhang, Chunlin Yang
1 citations
IEEE Transactions on Quantum Engineering
Matrix Theory and Algorithms
1.50
article

Binary Tree Block Encoding of Classical Matrix

Zexian Li, Xiaoming Zhang, Guofeng Zhang, Chunlin Yang
article en
1 citations

Abstract

State preparation and block-encoding are essential subroutines in quantum computing. The former provides basic encoding of quantum states, while the latter transforms classical data into a matrix representation within a quantum circuit. Some quantum advantages are built on the assumption that the subroutine– block encoding has been compiled in the quantum circuit, and this derives a problem of how to efficiently compile a block encoding. The resource trade-offs of block encoding, such as circuit size, subnormalization factor, compilation complexity (both time and space), and robustness against errors are central to its efficiency. In this work, the Binary Tree Block-Encoding (BITBLE) protocol is introduced, which optimizes these trade-offs. For a classical matrix in C<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2n× 2n</sup>, our approach reduces the compilation time to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</i>(n2<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2n</sup>) using n ancilla qubits, achieving superior resource trade-offs compared to existing methods. Numerical experiments further reveal that the approach outlined in BITBLE enhances compilation efficiency, resource scalability, and robustness against single-qubit gate errors in various standard data encoding tasks. Moreover, all algorithms are available as open-source.

IEEE Transactions on Quantum EngineeringVol. 7
Hong Kong Polytechnic University (HK), Harbin Engineering University (CN), South China Normal University (CN), Heilongjiang University (CN)
Openalex Percentile: Top 12%
Matrix Theory and Algorithms
1.50
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Binary Tree Block Encoding of Classical Matrix — Zexian Li, Xiaoming Zhang, et al. · IEEE Transactions on Quantum Engineering (2025) | TGRS Research Map | TGRS